Position:  Research engineer at INRIA – Grenoble, MORPHEO team

Date: The position is open and the candidate can start as soon as possible. Funding is for 12 months (renewable). A start in Mai 2025 could be possible.

Advisors: The retained candidate will be advised by Sergi Pujades (Morpheo INRIA Grenoble, France)  and Nikolas Hesse (Swiss Children's Rehab, University Children's hospital Zurich, Switzerland).

Context:

The ShapeUp Keiki  project is the third project of the ongoing ShapeUp Studies series, where humans in the ages ranging from newborn to 5 year old will be studied.

The purpose of these studies is to explore and develop ways to measure health and body composition from 2D and 3D images, and optical scans. These technologies aim to take a look inside areas of the human body hidden by our skin. The study will test if new imaging machines can provide useful and detailed information about various health and wellness risks. A cohort of voluntary participants will provide the data, creating the largest and most powerful description of optical body shape and its association to body composition, metabolic markers, function, and dietary intake.

Objectives

In this project the research engineer will work on the registration of the articulated body model SMIL [1, 2] to scan data (3D point clouds) of infants. An existing code base exists, which is suitable for adults, but infants present several additional challenges. Their poses can not be directed and automatic methods of pose detection will need to be studied. The shape of the participants of the ShapeUp Studies is also different from the shape of the population used to learn the SMIL model. The goal will be to create a more generic body model that better captures the variations in shape.

[1] Learning an Infant Body Model from RGB-D Data for Accurate Full Body Motion Analysis
Hesse, N., Pujades, S., Romero, J., Black, M. J., Bodensteiner, C., Arens, M., Hofmann, U. G., Tacke, U., Hadders-Algra, M., Weinberger, R., Müller-Felber, W., Schroeder, A. S.
In International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), September 2018

[2] Learning and Tracking the 3D Body Shape of Freely Moving Infants from RGB-D sequences
Hesse, N., Pujades, S., Black, M. J., Arens, M., Hofmann, U. G., Schroeder, A. S.
Transactions on Pattern Analysis and Machine Intelligence, 42 (10), Special Issue on RGB-D Vision, pp. 2540-2551, 2019.